Agrivoltaic Crop Yield Tradeoff Calculator

Agrivoltaic Food-and-Energy Land-Use Balance

Agrivoltaics places solar panels and crops on the same field. Rather than converting the entire field to a solar installation, a design leaves space for cultivation beneath or between panel rows. The central agrivoltaic tradeoff is additional electricity production versus the crop-yield reduction associated with panel shade.

This calculator gives farmers, landowners, planners, and researchers a transparent first-pass view of that crop-and-energy tradeoff. It is not a site design or feasibility study, but it shows how panel coverage, crop shade response, irradiance, and prices affect the modeled harvest and electricity outputs.

Formula: Agrivoltaic Crop Yield and Energy Tradeoff Model

This agrivoltaic model estimates agricultural and energy outcomes for a field of area A in hectares, comparing baseline crop production with a scenario in which panels cover part of the field.

1. Baseline crop yield and revenue for the field

• Field area (A): total cultivated area in hectares.
• Baseline crop yield (Y0): tonnes per hectare under current management without solar panels.
• Crop price: revenue per tonne of harvested crop.

For the field before agrivoltaic panels are installed, total crop yield is:

Baseline yield = A × Y₀ (tonnes)

and the crop revenue associated with that harvest is:

Baseline crop revenue = A × Y₀ × crop_price

2. Agrivoltaic shading, yield reduction, and shade sensitivity

• Panel coverage (f): percentage of the field area that is covered by solar panels.
• Shade sensitivity factor (s): a value between 0 and 1 that reflects how strongly the crop responds to shading on the panel-covered portion.

For this agrivoltaic yield estimate, the uncovered portion retains full yield and the covered portion has a proportional yield reduction determined by s. A larger shade sensitivity factor therefore produces a larger modeled yield loss for the same panel coverage.

The resulting total crop yield under panels is estimated as:

Y = A × Y₀ × (1 − (f / 100) × s)

where:

• A = area in hectares
• Y₀ = baseline yield per hectare (t/ha)
• f = panel coverage (%)
• s = shade sensitivity factor (0–1)

3. Agrivoltaic solar generation and electricity revenue

• Solar irradiance (G): average daily solar energy on a horizontal surface in kWh/m²/day.
• Panel efficiency (η): percentage of incoming solar energy converted to electricity.
• Electricity price (p): revenue per kWh of electricity sold or offset.

For the panel array in this agrivoltaic scenario, panel-covered area in m² is A × 10,000 × (f / 100). The model estimates daily energy output as:

E = A × 10,000 × (f / 100) × G × (η / 100) (kWh/day)

The corresponding daily energy revenue is:

Energy revenue = E × p

4. Agrivoltaic indicator for lower relative crop yield

To flag lower modeled crop yield in an agrivoltaic layout, the calculator applies a logistic indicator to the ratio of adjusted yield to baseline yield. The displayed percentage rises as that ratio falls below 0.8; it is a model indicator, not a measured probability of crop failure.

Use this agrivoltaic yield indicator comparatively:

• Lower values: the modeled yield remains closer to or above the 80% reference point.
• Higher values: the modeled yield is further below that reference point, so panel coverage and shade sensitivity deserve closer review.
• Not a field probability: the score does not replace crop trials, seasonal records, or an agronomic assessment.

Interpreting Agrivoltaic Crop Yield Tradeoff Results

After an agrivoltaic calculation, the results summarize modeled crop production, electricity output, and the revenue figures derived from each:

• Adjusted crop yield (t): estimated total harvest under the entered panel coverage and crop shade sensitivity.
• Baseline crop yield (t): expected total harvest without panels.
• Daily energy output (kWh): estimated daily electricity production from the covered area.
• Crop revenue and energy revenue: crop revenue is calculated from the entered yield and crop price, while energy revenue is calculated per day.
• Net revenue difference: the calculator's arithmetic difference between adjusted crop revenue plus daily energy revenue and baseline crop revenue.
• Yield drop risk indicator: a relative flag that increases as modeled yield falls below the 80% reference ratio.

For an agrivoltaic financial decision, first convert crop revenue and energy revenue to the same time basis. The form does not ask for harvest frequency or annual production, so its displayed net revenue difference should not be treated as a daily, seasonal, or annual profit figure without that additional conversion.

Worked Example: Agrivoltaic Field with 30% Panel Coverage

This agrivoltaic example uses the calculator's default field, crop, and solar assumptions to show how each output is derived.

• Field area A = 1 ha
• Panel coverage f = 30%
• Baseline crop yield Y₀ = 5 t/ha
• Crop price = $200/t
• Shade sensitivity factor s = 0.8
• Solar irradiance G = 5 kWh/m²/day
• Panel efficiency η = 18%
• Electricity price p = $0.10/kWh

Baseline crop outcome without agrivoltaic panels

Baseline yield:

Baseline yield = 1 × 5 = 5 t

Baseline crop revenue for that yield:

5 × 200 = $1,000

Agrivoltaic crop and solar outcome

Adjusted yield under panels:

Y = 1 × 5 × (1 − (30 / 100) × 0.8)

Y = 5 × (1 − 0.24) = 5 × 0.76 = 3.8 t

Crop revenue under panels:

3.8 × 200 = $760

Energy output:

Panel area = 1 × 10,000 × (30 / 100) = 3,000 m²

E = 3,000 × 5 × (18 / 100) = 3,000 × 5 × 0.18 = 2,700 kWh/day

Daily energy revenue:

2,700 × 0.10 = $270/day

Comparing agrivoltaic crop and energy outputs

In this example, the modeled harvest falls from 5 t to 3.8 t, reducing crop revenue for the stated yield from $1,000 to $760. The same layout produces an estimated 2,700 kWh/day and $270/day of energy revenue. Those crop and electricity revenues have different time bases, so a valid financial comparison requires the harvest period or annual crop production to be specified outside this calculator.

Vary panel coverage, crop shade sensitivity, irradiance, and prices to identify which assumptions most affect an agrivoltaic proposal. Coverage and shade sensitivity directly determine the modeled crop-yield change, while covered area, irradiance, and efficiency determine energy output.

Agrivoltaic Coverage and Shade-Response Scenarios

These agrivoltaic scenarios describe the directional patterns produced by the model; actual field response depends on crop, panel geometry, weather, and management.

Using the Agrivoltaic Crop Yield Tradeoff Calculator

Use this agrivoltaic calculator to test assumptions consistently before moving to site-specific crop and PV analysis.

• Start with local crop and solar data: Use field yield records, applicable crop prices, and irradiance estimates from reliable local or PV-design sources.
• Compare panel coverage levels: Run several coverage assumptions to see how quickly the modeled crop loss and electricity output change.
• Represent crop shade response carefully: Use a lower shade sensitivity factor only when it is supported by crop knowledge or local trial evidence.
• Use the relevant electricity value: Enter the price that reflects the intended sale, credit, or on-site offset arrangement.
• Align revenue periods: Convert harvest-based crop revenue and daily energy revenue to a common period before drawing economic conclusions.

Agrivoltaic Model Assumptions and Limitations

This agrivoltaic planning model deliberately simplifies field and solar-system behavior. Keep these assumptions and limitations in mind when reviewing its outputs:

• Uniform shading: The model treats all shaded area as having the same effect on yield. In practice, shading patterns vary by time of day, season, panel height, and row spacing.
• No seasonal variation: Inputs such as irradiance and yield are treated as averages. The model does not resolve month-by-month or seasonal effects.
• Single crop response: Crop response to shading is condensed into one shade sensitivity factor. Real responses can be non-linear, crop-specific, and management-dependent.
• Simple energy model: The energy estimate uses irradiance and panel efficiency only. It does not include temperature effects, inverter losses, soiling, curtailment, or downtime.
• Revenue timing is not normalized: Crop revenue follows the entered harvest yield, whereas energy revenue is daily. Investment costs, maintenance, financing, leasing, and incentives are not modeled.
• No environmental co-benefits: Potential changes in water use, microclimate, biodiversity, or soil conditions are not quantified.
• Site-specific design ignored: Panel tilt, orientation, tracking, row spacing, height, and structural design can materially affect real crop and energy performance but are not represented here.

Because of these agrivoltaic simplifications, use the calculator for preliminary exploration and education. Pair the results with crop-specific agronomic evidence and detailed engineering analysis before making an investment decision.

Agrivoltaic Data Sources and Further Reading

This agrivoltaic model is informed by research on crop performance under partial shade and on dual agricultural-solar land use. For a rigorous project assessment, consult peer-reviewed studies, local extension services, crop specialists, and solar developers familiar with agrivoltaic projects in the relevant region.

Use the calculator as a starting point for discussions with agronomists, energy planners, and financiers about configuring an agrivoltaic system that supports both crop production and renewable-energy goals.